Sci Rep. 2025 Jan 2;15(1):20. doi: 10.1038/s41598-024-84711-7.

ABSTRACT

The integration of drug molecular representations into predictive models for Drug Response Prediction (DRP) is a standard procedure in pharmaceutical research and development. However, the comparative effectiveness of combining these representations with genetic profiles for DRP remains unclear. This study conducts a comprehensive evaluation of the efficacy of various drug molecular representations employing cutting-edge machine learning models under various experimental settings. Our findings reveal that the inclusion of molecular representations from either PubChem fingerprints or SMILES can significantly enhance the performance of DRPs when used in conjunction with deep learning models. However, the optimal choice of drug molecular representation can vary depending on the predictive model and the specific DRP task. The insights derived from our study offer useful guidance on selecting the most suitable drug molecular representations for constructing efficient predictive models for DRPs, aiding for drug repurposing, personalized medicine, and new drug discovery.

PMID:39748003 | DOI:10.1038/s41598-024-84711-7

J Med Chem. 2025 Jan 2. doi: 10.1021/acs.jmedchem.4c02543. Online ahead of print.

ABSTRACT

Target identification is a critical stage in the drug discovery pipeline. Various computational methodologies have been dedicated to enhancing the classification performance of compound-target interactions, yet significant room remains for improving the recommendation performance. To address this challenge, we developed TarIKGC, a tool for target prioritization that leverages semantics enhanced knowledge graph (KG) completion. This method harnesses knowledge representation learning within a heterogeneous compound-target-disease network. Specifically, TarIKGC combines an attention-based aggregation graph neural network with a multimodal feature extractor network to simultaneously learn internal semantic features from biomedical entities and topological features from the KG. Furthermore, a KG embedding model is employed to identify missing relationships among compounds and targets. In silico evaluations highlighted the superior performance of TarIKGC in drug repositioning tasks. In addition, TarIKGC successfully identified two potential cyclin-dependent kinase 2 (CDK2) inhibitors with novel scaffolds through reverse target fishing. Both compounds exhibited antiproliferative activities across multiple therapeutic indications targeting CDK2.

PMID:39745279 | DOI:10.1021/acs.jmedchem.4c02543

Eur J Breast Health. 2025 Jan 1;21(1):63-73. doi: 10.4274/ejbh.galenos.2024.2024-11-2.

ABSTRACT

OBJECTIVE: The prevalence of breast cancer and gynaecological cancers is high, and these cancer types can occur consecutively as secondary cancers. The aim of our study is to determine the genes commonly expressed in these cancers and to identify the common hub genes and drug components.

MATERIALS AND METHODS: Gene intensity values of breast cancer, gynaecological cancers such as cervical, ovarian and endometrial cancers were used from the Gene Expression Omnibus database Affymetrix Human Genome U133 Plus 2.0 Array project. Using the linear modelling method included in the R LIMMA package, genes that differ between healthy individuals and cancer patients were identified. Hub genes were determined using cytoHubba in Cytoscape program. "ShinyGo 0.80" tool was used to determine the disease-specific biological KEGG pathways. Drug.MATADOR from the ShinyGo 0.80 tool was used to predict drug-target relationships.

RESULTS: The RecQ Like Helicase 4 and Family with Sequence Similarity 13 Member C genes were found to be similarly expressed in breast cancer and gynaecological cancers. Upon KEGG pathway analyses with hub genes, Drug.MATADOR analysis with hub genes related to cancer related pathways was performed. We have determined these gene/drug interactions: NBN (targeted by Hydroxyurea), EP300 (targeted by Acetylcarnitine) and MAPK14 (targeted by Salicylate and Dibutyryl cyclic AMP).

CONCLUSION: The drugs associated with hub genes determined in our study are not routinely used in cancer treatment. Our study offers the opportunity to identify the target genes of drugs used in breast and gynaecological cancers with the drug repurposing approach.

PMID:39744927 | DOI:10.4274/ejbh.galenos.2024.2024-11-2

ACS Infect Dis. 2024 Dec 31. doi: 10.1021/acsinfecdis.4c00693. Online ahead of print.

ABSTRACT

Protozoan parasite infections, particularly leishmaniasis, present significant public health challenges in tropical and subtropical regions, affecting socio-economic status and growth. Despite advancements in immunology, effective vaccines remain vague, leaving drug treatments as the primary intervention. However, existing medications face limitations, such as toxicity and the rise of drug-resistant parasites. This presents an urgent need to identify new therapeutic targets for leishmaniasis treatment. Understanding the complex life cycle of Leishmania and its survival in host macrophages can provide insights into potential targets for intervention. Current treatments, including antimonials, amphotericin B, and miltefosine, are constrained by side effects, costs, resistance, and reduced efficacy. Exploring novel therapeutic targets within the parasite's physiology, such as key metabolic enzymes or essential surface proteins, may lead to the development of more effective and less toxic drugs. Additionally, innovative strategies like drug repurposing, combination therapies, and nanotechnology-based delivery systems could enhance efficacy and combat resistance, thus improving anti-leishmanial therapies.

PMID:39737830 | DOI:10.1021/acsinfecdis.4c00693

Brief Bioinform. 2024 Nov 22;26(1):bbae696. doi: 10.1093/bib/bbae696.

ABSTRACT

Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and treatment of tuberculosis, making efforts to combat the spread of this global health burden more difficult. To accelerate anti-tuberculosis drug discovery, repurposing clinically approved or investigational drugs for the treatment of tuberculosis by computational methods has become an attractive strategy. In this study, we developed a virtual screening workflow that combines multiple machine learning and deep learning models, and 11 576 compounds extracted from the DrugBank database were screened against Mtb. Our screening method produced satisfactory predictions on three data-splitting settings, with the top predicted bioactive compounds all known antibacterial or anti-TB drugs. To further identify and evaluate drugs with repurposing potential in TB therapy, 15 screened potential compounds were selected for subsequent computational and experimental evaluations, out of which aldoxorubicin and quarfloxin showed potent inhibition of Mtb strain H37Rv, with minimal inhibitory concentrations of 4.16 and 20.67 μM/mL, respectively. More inspiringly, these two compounds also showed antibacterial activity against multidrug-resistant TB isolates and exhibited strong antimicrobial activity against Mtb. Furthermore, molecular docking, molecular dynamics simulation, and the surface plasmon resonance experiments validated the direct binding of the two compounds to Mtb DNA gyrase. In summary, our effective comprehensive virtual screening workflow successfully repurposed two novel drugs (aldoxorubicin and quarfloxin) as promising anti-Mtb candidates. The verification results provide useful information for the further development and clinical verification of anti-TB drugs.

PMID:39737570 | DOI:10.1093/bib/bbae696

Indian J Med Res. 2024 Nov;160(5):466-478. doi: 10.25259/IJMR_569_2024.

ABSTRACT

Background & objectives The emergence of drug resistance in leishmaniasis has remained a concern. Even new drugs have been found to be less effective within a few years of their use. Coupled with their related side effects and cost-effectiveness, this has prompted the search for alternative therapeutic options. In this study, the Computer Aided Drug Design (CADD) approach was used to repurpose already existing drugs against Leishmania major. The enzyme lanosterol 14-alpha demethylase (CYP51), in L. major, was chosen as the drug target since it is a key enzyme involved in synthesizing ergosterol, a crucial component of the cell membrane. Methods A library of 1615 FDA-approved drugs was virtually screened and docked with modeled CYP51 at its predicted binding site. The drugs with high scores and high affinity were subjected to Molecular Dynamics (MD) simulations for 100 ns. Finally, the compounds were tested in vitro using an MTT [3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide] assay against the promastigotes of L. major. Results Computational screening of FDA-approved drugs identified posaconazole and isavuconazole as promising candidates, as both drugs target the CYP51 enzyme in fungi. Molecular dynamics (MD) simulations demonstrated that both drugs form stable complexes with the target enzyme. In vitro studies of posaconazole and isavuconazole against promastigotes of L. major demonstrated significant efficacy, with IC50 values of 2.062±0.89 µg/ml and 1.202±0.47 µg/ml, respectively. Interpretation & conclusions The study showed that the existing FDA-approved drugs posaconazole and isavuconazole can successfully be repurposed for treating L. major by targeting the CYP51 enzyme, demonstrating significant efficacy against promastigotes.

PMID:39737513 | DOI:10.25259/IJMR_569_2024

Iran Biomed J. 2024 Dec 1;28(7):250.

NO ABSTRACT

PMID:39736811

Sci Rep. 2024 Dec 28;14(1):31461. doi: 10.1038/s41598-024-82967-7.

ABSTRACT

Wnt signaling is a critical pathway implicated in cancer development, with Frizzled proteins, particularly FZD10, playing key roles in tumorigenesis and recurrence. This study focuses on the potential of repurposed FDA-approved drugs targeting FZD10 as a therapeutic strategy for nasopharyngeal carcinoma (NPC). The tertiary structure of human FZD10 was constructed using homology modeling, validated by Ramachandran plot and ProQ analysis. Virtual screening of 1,094 FDA-approved drugs identified 17 potential inhibitors, with prazosin, rilpivirine, doxazosin, and nicergoline demonstrating significant cytotoxicity against NPC cells. Further molecular dynamics simulations and binding energy analyses confirmed the stable binding of these drugs to FZD10. The results suggest that these repurposed drugs could serve as promising candidates for targeted NPC therapy, warranting further investigation.

PMID:39733096 | DOI:10.1038/s41598-024-82967-7

Comput Biol Chem. 2024 Dec 25;115:108329. doi: 10.1016/j.compbiolchem.2024.108329. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Castration-resistant prostate cancer (CRPC) is caused by resistance to androgen deprivation treatment and leads to the death of patients and there is almost no chance of survival. Therefore, finding a cure to overcome CRPC is challenging and important, but discovering a new drug is very time-consuming and expensive. To overcome these problems, we used Drug repositioning (drug repurposing) strategy in this study.

METHODS: Gene expression data of CRPC and primary prostate samples were extracted from the GEO database to identify DEGs. Pathway enrichment was performed to find the role of DEGs in signaling pathways. To identify hub proteins, the PPI network was reconstructed and analyzed. drug candidates were identified and to select the most effective drug, molecular docking analysis, and molecular dynamics simulation were performed. Then MTT and qRT-PCR tests were performed to check the effectiveness of the selected drug.

RESULTS: A total of 152 upregulated DEGs and 343 downregulated DEGs were identified, and after PPI network analysis, IKBKB, SNAP23, MYC, and NOTCH1 genes were introduced as hubs. drug candidates for IKBKB were identified and by examining the results of docking screening and molecular dynamics, sulfasalazine was selected as the most effective drug. Laboratory analyses proved the effectiveness of this drug and a decrease in the expression of all target genes was observed.

CONCLUSION: In this study, IKBKB key protein were identified in CRPC, and sulfasalazine was selected as a suitable candidate for drug repositioning and its effectiveness was confirmed through tests.

PMID:39731827 | DOI:10.1016/j.compbiolchem.2024.108329

Vet Res Commun. 2024 Dec 28;49(1):59. doi: 10.1007/s11259-024-10628-1.

ABSTRACT

Camel mastitis especially caused by Staphylococcus aureus (S. aureus), is a major risk to animal health and milk production. The current investigation evaluated the antibiotic susceptibility and virulence factors of S. aureus isolates from subclinical mastitis in camels. A total of 384 milk samples were collected and submitted to isolate S. aureus. The S. aureus isolates exhibiting resistance to Penicillin and Cefoxitin disc on Kirby-Bauer disc diffusion method were considered as β-lactam resistant S. aureus (BRSA) and methicillin-resistant S. aureus (MRSA) which were further confirmed by PCR targeting blaZ and mecA genes, respectively. The results showed that S. aureus was found in 57.06% of subclinical (SCM) positive camel milk samples. A high molecular prevalence of BRSA and MRSA were found to be 48.51% and 46.53% respectively depicting that treating these infections is challenging due to their high resistance levels. The phylogenetic analysis revealed a significant resemblance of the study isolates with each other and with already reported sequences from different countries which shows the potential for the spread of pathogen. Virulence profiling of antibiotic resistance strains showed the presence of virulence markers (nuc and coag genes), intercellular adhesion genes (icaA, icaD), Panton-Valentine leukocidin (pvl) gene, and enterotoxin-producing genes including sea, seb, sec, and sed. In-vitro antibiotic susceptibility testing revealed that the most resistant antibiotic group was penicillin followed by aminoglycosides and cephalosporins. Drug repurposing analysis of different non-antibiotics for combination therapies with resistant antibiotics was done to combat the S. aureus isolates harboring the mecA and blaZ genes. The results revealed the synergistic effect of amoxicillin, sulfamethoxazole, gentamicin, and doxycycline with ketoprofen, amikacin with flunixin meglumine, and gentamicin with N-acetylcysteine (NAC) against study isolates. The current investigation provides the status of antibiotic-resistant strains and virulence factors of S. aureus in the udder of dromedary camels. The combinational therapy of resistant antibiotics with non-antibiotics provides a potential therapeutic option for the treatment of resistant strains.

PMID:39731665 | DOI:10.1007/s11259-024-10628-1

Sci Rep. 2024 Dec 28;14(1):31006. doi: 10.1038/s41598-024-82177-1.

ABSTRACT

Articular cartilage has a limited regenerative capacity, resulting in poor spontaneous healing of damaged tissue. Despite various scientific efforts to enhance cartilage repair, no single method has yielded satisfactory results. With rising drug development costs, drug repositioning has emerged as a viable alternative. This study aimed to identify a drug capable of improving cartilage defects by analyzing chondrogenesis-related microarray data from the Gene Expression Omnibus (GEO) public database. We utilized datasets GSE69110, GSE107649, GSE111822, and GSE116173 to identify genes associated with cartilage differentiation, employing StringTie for differential gene expression analysis and extracting drug data from the Drug-Gene Interaction database. Additionally, we aimed to verify the cartilage regeneration potential of the identified drug through experiments using cellular and animal models. We evaluated the effects of aripiprazole on adipose-derived mesenchymal stem cells (ADMSCs) and chondrocytes using qRT-PCR and a 3D pellet culture system. In vivo, we assessed cartilage restoration by combining aripiprazole with a scaffold and implanting it into artificially induced cartilage defects in Sprague-Dawley rats. Subsequent mRNA sequencing provided insights into the mechanistic pathways involved. Our results showed that aripiprazole significantly increased mRNA expression of COL2A1 and SOX9, markers of chondrogenesis, and promoted chondrogenic condensation in vitro. Furthermore, aripiprazole effectively enhanced cartilage regeneration in the rat model. KEGG pathway and Gene Ontology Biological Processes (GOBP) analyses of the mRNA sequencing data revealed that aripiprazole upregulated genes related to ribosomes and cytoplasmic translation, thereby facilitating chondrogenesis. In conclusion, our findings suggest that aripiprazole is a promising candidate for improving damaged cartilage, offering a novel approach to cartilage regeneration.

PMID:39730885 | DOI:10.1038/s41598-024-82177-1

PLoS One. 2024 Dec 27;19(12):e0315245. doi: 10.1371/journal.pone.0315245. eCollection 2024.

ABSTRACT

The increasing utilization of deep learning models in drug repositioning has proven to be highly efficient and effective. In this study, we employed an integrated deep-learning model followed by traditional drug screening approach to screen a library of FDA-approved drugs, aiming to identify novel inhibitors targeting the TNF-α converting enzyme (TACE). TACE, also known as ADAM17, plays a crucial role in the inflammatory response by converting pro-TNF-α to its active soluble form and cleaving other inflammatory mediators, making it a promising target for therapeutic intervention in diseases such as rheumatoid arthritis. Reference datasets containing active and decoy compounds specific to TACE were obtained from the DUD-E database. Using RDKit, a cheminformatics toolkit, we extracted molecular features from these compounds. We applied the GraphConvMol model within the DeepChem framework, which utilizes graph convolutional networks, to build a predictive model based on the DUD-E datasets. Our trained model was subsequently used to predict the TACE inhibitory potential of FDA-approved drugs. From these predictions, Vorinostat was identified as a potential TACE inhibitor. Moreover, molecular docking and molecular dynamics simulation were conducted to validate these findings, using BMS-561392 as a reference TACE inhibitor. Vorinostat, originally an FDA-approved drug for cancer treatment, exhibited strong binding interactions with key TACE residues, suggesting its repurposing potential. Biological evaluation with RAW 264.7 cell confirmed the computational results, demonstrating that Vorinostat exhibited comparable inhibitory activity against TACE. In conclusion, our study highlights the capability of deep learning models to enhance virtual screening efforts in drug discovery, efficiently identifying potential candidates for specific targets such as TACE. Vorinostat, as a newly identified TACE inhibitor, holds promise for further exploration and investigation in the treatment of inflammatory diseases like rheumatoid arthritis.

PMID:39729480 | DOI:10.1371/journal.pone.0315245

Trop Med Infect Dis. 2024 Nov 25;9(12):288. doi: 10.3390/tropicalmed9120288.

ABSTRACT

Tuberculosis (TB) is a global health challenge associated with considerable levels of illness and mortality worldwide. The development of innovative therapeutic strategies is crucial to combat the rise of drug-resistant TB strains. DNA Gyrase A (GyrA) and serine/threonine protein kinase (PknB) are promising targets for new TB medications. This study employed techniques such as similarity searches, molecular docking analyses, machine learning (ML)-driven absolute binding-free energy calculations, and molecular dynamics (MD) simulations to find potential drug candidates. By combining ligand- and structure-based methods with ML principles and MD simulations, a novel strategy was proposed for identifying small molecules. Drugs with structural similarities to existing TB therapies were assessed for their binding affinity to GyrA and PknB through various docking approaches and ML-based predictions. A detailed analysis identified six promising compounds for each target, such as DB00199, DB01220, DB06827, DB11753, DB14631, and DB14703 for GyrA; and DB00547, DB00615, DB06827, DB14644, DB11753, and DB14703 for PknB. Notably, DB11753 and DB14703 show significant potential for both targets. Furthermore, MD simulations' statistical metrics confirm the drug-target complexes' stability, with MM-GBSA analyses underscoring their strong binding affinity, indicating their promise for TB treatment even though they were not initially designed for this disease.

PMID:39728815 | DOI:10.3390/tropicalmed9120288

Metabolites. 2024 Dec 20;14(12):719. doi: 10.3390/metabo14120719.

ABSTRACT

BACKGROUND: Paclitaxel is a widely used anticancer drug for ovarian, lung, breast, and stomach cancers; however, its clinical use is often limited by the side effects of peripheral neuropathy. This study evaluated the effects of Cyperus rotundus (C. rotundus) extract and its active metabolite, α-cyperone, on paclitaxel-induced neuropathic pain.

METHODS: The oral administration of C. rotundus extract at doses of 500 mg/kg and intraperitoneal administration of α-cyperone at doses of 480 and 800 μg/kg prevented both the development of cold and mechanical pain.

RESULTS: The gene and protein expressions of tyrosine hydroxylase and noradrenergic receptors (α1- and α2-adrenergic), which were upregulated by paclitaxel, were significantly downregulated in the C. rotundus extract-treated group. In the locus coeruleus region of the mouse brain, C. rotundus extract administration also reduced the elevated expression of tyrosine hydroxylase induced by paclitaxel. The concentration of α-cyperone in C. rotundus extract was quantified using high-performance liquid chromatography (HPLC). In the group treated with α-cyperone, at levels corresponding to its content in C. rotundus, both cold and mechanical allodynia were effectively prevented.

CONCLUSIONS: This study suggests that α-cyperone shows potential as a preventive agent for paclitaxel-induced neuropathic pain.

PMID:39728499 | DOI:10.3390/metabo14120719

J Fungi (Basel). 2024 Dec 15;10(12):871. doi: 10.3390/jof10120871.

ABSTRACT

This review explores current advancements and challenges in antifungal therapies amid rising fungal infections, particularly in immunocompromised patients. We detail the limitations of existing antifungal classes-azoles, echinocandins, polyenes, and flucytosine-in managing systemic infections and the urgent need for alternative solutions. With the increasing incidence of resistance pathogens, such as Candida auris and Aspergillus fumigatus, we assess emerging antifungal agents, including Ibrexafungerp, T-2307, and N'-Phenylhydrazides, which target diverse fungal cell mechanisms. Innovations, such as nanoparticles, drug repurposing, and natural products, are also evaluated for their potential to improve efficacy and reduce resistance. We emphasize the importance of novel approaches to address the growing threat posed by fungal infections, particularly for patients with limited treatment options. Finally, we briefly examine the potential use of artificial intelligence (AI) in the development of new antifungal treatments, diagnoses, and resistance prediction, which provides powerful tools in the fight against fungal pathogens. Overall, we highlight the pressing need for continued research to advance antifungal treatments and improve outcomes for high-risk populations.

PMID:39728367 | DOI:10.3390/jof10120871

In Silico Pharmacol. 2024 Dec 24;13(1):5. doi: 10.1007/s40203-024-00293-2. eCollection 2025.

ABSTRACT

Drug repurposing is necessary to accelerate drug discovery and meet the drug needs. This study investigated the possibility of using fluvoxamine to inhibit the cellular metabolizing enzyme NUDT5 in breast cancer. Computational and experimental techniques were used to evaluate the structural flexibility, binding stability, and chemical reactivity of the drugs. These findings indicated that fluvoxamine effectively suppressed the activity of NUDT5, as evidenced by a binding score of - 8.514 kcal/mol. Furthermore, the binding positions of fluvoxamine and NUDT5 were optimized. Fluvoxamine attachment to the active sites of Trp28, Trp46, Glu47, Arg51, Arg84, and Leu98 in NUDT5 has been shown to alter the metabolism of ADPr. These alterations play a role in ATP production in the breast cancer cells. In addition, an MTT assay conducted on the MCF-7 cell line using fluvoxamine revealed an IC50 value of 53.86 ± 0.05 µM. Fluvoxamine-induced apoptosis was confirmed as evidenced by AO/EtBr and DAPI staining.

GRAPHICAL ABSTRACT: Effect of fluvoxamine on breast cancer cells.

PMID:39726906 | PMC:PMC11668718 | DOI:10.1007/s40203-024-00293-2

Eur J Pharmacol. 2024 Dec 24:177231. doi: 10.1016/j.ejphar.2024.177231. Online ahead of print.

ABSTRACT

Multidrug resistance (MDR) remains a significant obstacle in cancer treatment, primarily attributable to the overexpression of ATP-binding cassette (ABC) transporters such as ABCB1 and ABCG2 within cancer cells. These transporters actively diminish the effectiveness of cytotoxic drugs by facilitating ATP hydrolysis-dependent drug efflux, thereby reducing intracellular drug accumulation. Given the absence of approved treatments for multidrug-resistant cancers and the established benefits of combining tyrosine kinase inhibitors (TKIs) with conventional anticancer drugs, we investigate the potential of vodobatinib, a potent c-Abl TKI presently in clinical trials, to restore sensitivity to chemotherapeutic agents in multidrug-resistant cancer cells overexpressing ABCB1 and ABCG2. Results indicate that vodobatinib, administered at sub-toxic concentrations, effectively restores the sensitivity of multidrug-resistant cancer cells to cytotoxic drugs in a concentration-dependent manner. Moreover, vodobatinib enhances drug-induced apoptosis in these cells by inhibiting the drug-efflux function of ABCB1 and ABCG2, while maintaining their expression levels. Moreover, we found that while vodobatinib enhances the ATPase activity of ABCB1 and ABCG2, the overexpression of these transporters does not induce resistance to vodobatinib. These results strongly suggest that increased levels of ABCB1 or ABCG2 are unlikely to play a significant role in the development of resistance to vodobatinib in cancer patients. Overall, our findings unveil an additional pharmacological facet of vodobatinib against ABCB1 and ABCG2 activity, suggesting its potential incorporation into combination therapy for a specific subset of patients with tumors characterized by high ABCB1 or ABCG2 levels. Further investigation is warranted to fully elucidate the clinical implications of this therapeutic approach.

PMID:39725134 | DOI:10.1016/j.ejphar.2024.177231

Arch Microbiol. 2024 Dec 26;207(1):18. doi: 10.1007/s00203-024-04205-y.

ABSTRACT

Klebsiella pneumoniae is a leading cause of anti-microbial resistance in healthcare-associated infections that have posed a severe threat to neonatal and wider community. The escalating crises of antibiotic resistance have compelled researchers to explore an innovative arsenal beginning from natural resources to chemical modifications in order to overcome the ever-increasing resistance issues. The present review highlights the drug discovery efforts with a special focus on cutting-edge strategies in the hunt for potential drug candidates against MDR/XDR Klebsiella pneumoniae. Nature's bounty constituting plant extracts, essential oils, fungal extracts, etc. holds promising anti-bacterial potential especially when combined with existing antibiotics. Further, enhancing these natural products with synthetic moieties has improved their effectiveness, creating a bridge between the natural and synthetic world. Conversely, the synthetically modified novel scaffolds have been also designed to meticulously target specific sites. Furthermore, we have also elaborated various emerging strategies for broad-spectrum infections caused by K. pneumoniae, which include anti-microbial peptides, nanotechnology, drug repurposing, bacteriophage, photodynamic, and multidrug therapies. This review further addresses the challenges confronted by the research community and the future way forward in the field of drug discovery against multi-resistant bacterial infections.

PMID:39724243 | DOI:10.1007/s00203-024-04205-y

Protein Sci. 2025 Jan;34(1):e70006. doi: 10.1002/pro.70006.

ABSTRACT

This study focuses on spastic paraplegia type 50 (SPG50), an adapter protein complex 4 deficiency syndrome caused by mutations in the adapter protein complex 4 subunit mu-1 (AP4M1) gene, and on the downstream alterations of the AP4M1 protein. We applied a battery of heterogeneous computational resources, encompassing two in-house tools described here for the first time, to (a) assess the druggability potential of AP4M1, (b) characterize SPG50-associated mutations and their 3D scenario, (c) identify mutation-tailored drug candidates for SPG50, and (d) elucidate their mechanisms of action by means of structural considerations on homology models of the adapter protein complex 4 core. Altogether, the collected results indicate R367Q as the mutation with the most promising potential of being corrected by small-molecule drugs, and the flavonoid rutin as best candidate for this purpose. Rutin shows promise in rescuing the interaction between the AP4M1 and adapter protein complex subunit beta-1 (AP4B1) subunits by means of a glue-like mode of action. Overall, this approach offers a framework that could be systematically applied to the investigation of mutation-wise molecular mechanisms in different hereditary spastic paraplegias, too.

PMID:39723768 | DOI:10.1002/pro.70006

Neurourol Urodyn. 2024 Dec 26. doi: 10.1002/nau.25651. Online ahead of print.

ABSTRACT

INTRODUCTION: Interstitial cystitis/bladder pain syndrome (IC/BPS) is a debilitating pain condition of unknown etiology. Effective therapies for this condition could not have been developed in the last century. Drug repurposing is a practical strategy for enhancing patient access to successful therapies. It is an approach for discovering novel applications for licensed or investigational pharmaceuticals that extend beyond the initial medical indication. This work aims to identify repurposable medications through bioinformatics to discover potential drugs or compounds that can reverse the IC/BPS disease signature.

METHODS AND MATERIAL: The analysis involved examining the differentially expressed genes in IC/BPS patients with two distinct disease phenotypes (Hunner's lesion disease, non-Hunner's lesion disease) and controls using the datasets GSE11783, GSE28242, and GSE57560. The goal was to assess the reversal of the disease signature on the L1000CDS2 and cMAP platforms.

RESULTS: Twenty-one compounds were repurposed, consisting of 11 small molecules, 10 chemical compounds, 3 natural products, and 6 FDA-approved drugs, currently used for clinical indications such as cancer, myelofibrosis, and diabetes.

DISCUSSION: Bioinformatics can be useful for identifying therapeutic agents for IC/BPS by accessing and processing big data on molecular and cellular levels. Prospective in vivo experiments must validate repurposed drugs. The expansion of large-scale genome sequencing, gene expression studies, and clinical data for IC/BPS will improve successful drug selection.

PMID:39723619 | DOI:10.1002/nau.25651